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IN-PASS: Intelligent Navigation, Planning, and Autonomy for Swarm Systems

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC20C0314
Agency Tracking Number: 205760
Amount: $124,805.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: T4
Solicitation Number: STTR_20_P1
Timeline
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-08-12
Award End Date (Contract End Date): 2021-09-30
Small Business Information
7852 Walker Drive
Greenbelt, MD 20770-3208
United States
DUNS: 110592016
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Ken Center
 (240) 391-3310
 ken.center@orbitlogic.com
Business Contact
 Ella Herz
Phone: (301) 982-6234
Email: ella.herz@orbitlogic.com
Research Institution
 University of Colorado Boulder
 
1111 Engineering Dr
Boulder, CO 80309-0000
United States

 Nonprofit College or University
Abstract

Orbit Logic is teamed with the University of Colorado at Boulder to develop Intelligent Navigation, Planning, and Autonomy for Swarm Systems (IN-PASS). The proposed technology builds on proven software ndash; to enable flexible composition of collaborative mission concepts assessed in an open simulation environment. The focus of IN-PASS is rover autonomous navigation ndash; specifically development of onboard algorithms to reduce uncertainty in rover localization minimizing use of onboard resources. The solution will apply to a heterogeneous swarm of lunar orbital and surface assets.nbsp; For example, a constellation of CubeSats provides GPS-like navigation services to aid onboard estimation of rover state to inform onboard planning. When a limited number of satellites are deployed, the constellation cannot continually provide measurement support; hence the system will use Event-Trigged Distributed Data Fusion (ET-DDF) between swarm assets to maintain a high-degree of state knowledge with minimal data exchange. Team awareness is critical to coordinating activities to achieve mission goals while optimizing use of asset resources and responding to dynamic events. Mission plan optimization determines resources to engage during certain mission phases to ensure success. This is particularly true for inter-asset communications or localization, which employ hardware components and processing that utilize significant stored energy. This STTR focuses on development of onboard planning algorithms based on formal methods that determine the degree of resource utilization required to successfully achieve mission activities. Earth-based mission control operators or astronauts participating in-the-loop with these swarms will specify mission goals. The proposed research considers the most effective interaction between humans and swarm elements including specification of goals, interactive feedback on viability of the humanrsquo;s requests, and ultimate delivery of the resulting science to the human.

* Information listed above is at the time of submission. *

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